0430f0811e0a5cd377b9c377e915bbbbb1572ce7,pycox/models/deephit.py,DeepHit,predict_cif,#DeepHit#Any#Any#Any#Any#Any#Any#,372

Before Change

        pmf = self.predict_pmf(input, batch_size, eval_, to_cpu, num_workers, False)
        cif = pmf.cumsum(1)
        if numpy is None:
            if tuplefy(input).type() is np.ndarray:
                cif = cif.cpu().numpy()
        elif numpy is True:
                cif = cif.cpu().numpy()
        return cif

    def predict_survival_function(self, input, batch_size=8224, eval_=True, to_cpu=False,
                                  num_workers=0, numpy=None):
        Predict survival function (survive all of the event types).

After Change

        
        pmf = self.predict_pmf(input, batch_size, False, eval_, to_cpu, num_workers)
        cif = pmf.cumsum(1)
        return array_or_tensor(cif, numpy, input)

    def predict_pmf(self, input, batch_size=8224, numpy=None, eval_=True,
                     to_cpu=False, num_workers=0):
        Predict the probability mass fuction (PMF) for `input`.

Instances